The Shift Toward Smarter Shops: Real-World Stories of Data-Driven Manufacturing
Data-driven manufacturing is no longer theoretical. In this special issue of 91±¬ÁÏÍø, we present five stories of how digital tools — including AI co-pilots, predictive analytics, and real-time feedback — optimize operations and reduce downtime.
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These automated guided vehicles (AGVs) at DMG MORI’s assembly plant in Tortona, Italy, will soon serve as active transport systems to guide DMG MORI’s universal turning centers through different stages of the assembly process. Source: Brent Donaldson, MMS
The French phrase “déjà rêvé,” or “already dreamt,” is the feeling that you’ve dreamed about an experience you are having in the moment. Like déjà vu with a surreal twist, this feeling snuck up on me during a recent tour of DMG MORI’s assembly plant in Tortona, Italy. I was standing in the middle of a large, open, white-floored assembly room lined with massive automated guided vehicles (AGVs) sitting dormant in neat rows around the edge of the facility. When these slow-moving robots are activated in the coming months, they will serve as active transport systems, using optical navigation and laser scanning technologies to guide DMG MORI’s universal turning centers through different stages of the assembly process. Standing in the middle of these towering robots-at-rest evoked a strong childhood vision of the future.
Like the steady pace of these AGVs — which travel approximately 1.77 inches per minute and are already in use at the company’s Pfronten, Germany facility — we are clearly moving toward a collective vision of fully-automated production. From small job shops to large captive operations, it is now common to find connected devices offering instant feedback loops, increasingly underpinned by artificial intelligence (AI). Robots and cobots are nearly ubiquitous. Digital twins and simulation are growing increasingly sophisticated. And at the center of it all is data.
Our May, 2025 print edition offers five stories that unpack data-driven manufacturing and showcase its role in a variety of shop settings. Incidentally, this is the first print edition of 91±¬ÁÏÍø in recent memory dedicated solely to a single technology topic (albeit a broad one) and how that technology is being deployed in real time at American companies.
Let’s start with AI’s role in discrete part manufacturing — a topic prone to wildly varying interpretations within our industry. “Enhancing the Shop Floor With AI” (page 48) examines AI’s function across a host of production steps, beginning with its ability to serve as a “CAM co-pilot.” MMS readers are by now likely familiar with AI technologies that help generate tool paths (arguably AI’s most common use today outside of predictive maintenance) but here we explore its ability to detect early signs of chatter, optimize energy use and even enhance ergonomics through human simulation. The article shows how AI can be used to amplify human expertise and allow shop-specific knowledge to seamlessly integrate with the shop floor. This article is clear evidence that AI’s capabilities will only grow as digitalization becomes commonplace in job shops, producing ever-higher quantities of AI fuel: data.
Our next story takes this principle and extends it into the CNC itself. On page 42, Senior Associate Editor Eli Plaskett offers an intriguing look at Gemineers, a German startup that has developed a machine-connected digital twin that captures spindle loads, axis motion and positional errors with ±10-micron resolution to provide real-time process insights. Gemineers’ closed-loop system doesn’t just simulate machining, it also predicts errors, diagnoses failures mid-cut and refines future production runs. By offering real-time feedback in addition to foresight, the company believes its digital twin is precise enough to minimize the need for quality inspection or at least shift its role.
Closer to home, LeClaire Manufacturing, an aluminum casting and precision component shop in Bettendorf, Iowa, offers a different method of tracing issues back to their root cause. On page 62, Senior Associate Editor Evan Doran profiles the company’s Caddis system, a custom, cloud-connected software platform developed by LeClaire that tracks essential metrics such as uptime, temperature, amperage and cycle times, then sets alerts based on deviations from each metric’s norm. By tracking essential data to inform real-time decisions, the Caddis system has reduced setup times by two-thirds, decreased unplanned downtime and increased machine utilization by 38% — all without investing in new equipment.
On page 54, Doran walks us through a different challenge when tracking data — how to make sense of it within a complex, interconnected workflow on the shop floor. While MachineMetrics has long been known as a machine monitoring provider, the company is evolving its platform into something closer to a manufacturing execution system (MES) by integrating machine data with ERP schedules and AI-driven analytics. In both high-production and high-mix settings, this rich data stew can be contextualized to provide real-time feedback on cycle times, tool load anomalies and production delays. Doran’s article shows how meaning, not just volume, represents data’s true power on the shop floor.
Finally, on page 58, Doran spotlights how Woodward Inc., a precision manufacturer serving the aerospace and power generation industries, has evolved into a true “digital factory” through Caron Engineering’s MiConnect software. Previously, Woodward spent months building custom APIs to connect its CNC machines to its SCADA software, but today, MiConnect allows them to not only streamline data collection from a diverse array of controls but also supports bidirectional feedback and facilitates real-time adjustments, robotic integration and automated tool compensations across sites. The story also reveals why this level of digital integration requires sophisticated engineers to helm the controls and showcases the critical importance of human expertise to maximize data-driven manufacturing technologies.
So what do these stories tell us?
Each of the companies highlighted in this issue uses data to enhance, not eclipse, human ingenuity. They use data as a force multiplier, but in distinct ways for distinct purposes. From small shops building their own monitoring systems to global producers synchronizing multi-plant operations, the lesson that connects these stories is clarity. The ability to see what’s happening at your shop is important, but understanding why it’s happening allows you to refine your processes and, ultimately, redefine what’s possible.
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